Automated tissue sectioning system with cut quality prediction

Abstract

The sectioning system includes a chuck assembly configured to receive a tissue block, a cutting assembly configured to remove a tissue section from the tissue block, at least one sensor configured to sense data regarding the behavior of one or more components of at least one of the chuck assembly or the cutting assembly, and a control system. The control system is configured to receive data from the at least one sensor, determine whether the data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly, and output a signal if it is determined that the data from the at least one sensor is not indicative of normal behavior of the one or more components.

Description

[Technical field]

[0001] (CROSS REFERENCE TO RELATED APPLICATIONS) This application claims the benefit of and priority to U.S. Provisional Patent Application No. 63 / 265,747, filed December 20, 2021, and U.S. Utility Patent Application No. 18 / 085,383, filed December 20, 2022, the contents of which are incorporated herein by reference in their entireties.

[0002] The present disclosure relates to automated systems and methods for sectioning tissue from biological tissue blocks, and more particularly to systems and methods that provide prediction of microtome cut quality. [Background technology]

[0003] Traditional microtomy, the production of micron-thin tissue sections for microscopic viewing, is a delicate, time-consuming manual task. Recent advances in digital imaging of tissue sample sections make it desirable to slice specimen blocks very quickly. As an example, when tissue is sectioned as part of a clinical procedure, time is a critical variable in improving patient treatment. Every minute that can be saved during sectioning of tissue for intraoperative applications in anatomic pathology, such as when inspecting the margins of a lung cancer to determine if sufficient tissue has been removed, is of clinical benefit. To rapidly generate large numbers of sample sections, it is desirable to automate the process of cutting the tissue sections from the supporting tissue block with a microtome blade and facilitating the transfer of the cut tissue sections to slides.

[0004] Every minute that can be saved during sectioning of tissue for intraoperative applications in anatomical pathology can be important. Poor cut quality of sectioned tissue can slow down the process while the operator or laboratory researcher attempts to determine the potential source of the poor cut quality. It would be advantageous to provide an automated system that could increase the predictive ability of at least one source of poor cut quality, thereby saving time. Summary of the Invention [Means for solving the problem]

[0005] A need exists for improved systems and methods for tissue sample preparation. The present disclosure is directed to a solution to address this need, in addition to having other desirable characteristics.

[0006] The present disclosure relates to a sectioning system including a chuck assembly configured to receive a tissue block; a cutting assembly configured to remove a tissue section from the tissue block; at least one sensor configured to sense data regarding the dynamics of one or more components of at least one of the chuck assembly or the cutting assembly; and a control system configured to receive data from the at least one sensor, determine whether the data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly, and output a signal if it is determined that the data from the at least one sensor does not indicate normal behavior of the one or more components.

[0007] In some embodiments, the present disclosure relates to a sectioning system, where the signal is a control signal to one or more components of at least one of a chuck assembly or a cutting assembly to adjust an operating parameter of the one or more components. In some embodiments, the present disclosure relates to a sectioning system, where the signal is an alert to a user. In some embodiments, the present disclosure relates to a sectioning system, where the signal is a control signal to suspend operation of the sectioning system. In some embodiments, the present disclosure relates to a sectioning system, where a control system is configured to receive data from at least one sensor and determine that the data does not indicate normal behavior of the one or more components when the data exceeds a predefined limit value of baseline data indicative of normal behavior of the one or more components. In some embodiments, the present disclosure relates to a sectioning system, where the control system is configured to determine whether the dynamics of one or more components exceed a predetermined threshold in a selected frequency band and output a signal to correct the source of the dynamics exceeding the predetermined threshold. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is a camera including an image sensor configured to capture at least one of still images, video, or high speed images, and the data includes at least one of still images, video, or high speed images. In some embodiments, the present disclosure relates to a sectioning system, where the sectioning system further includes a motor configured to excite at least one of the chuck assembly or the cutting assembly with a predefined vibration signal, and the control system is configured to measure data using the at least one sensor and obtain baseline data of at least one of the chuck assembly or the cutting assembly.In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is one or more of an image sensor, a video sensor, a high speed image sensor, a laser Doppler vibrometer, an acoustic sensor, or a force-based sensor. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is configured to capture image or live feed image data and monitor performance of the sectioning system as a function of the image or live feed image data, and where the control system is configured to adjust operating parameters of at least one of the chuck assembly or the cutting assembly as a function of the image or live feed image data. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is an image sensor, where the sectioning system further includes an illumination system that provides illumination at various wavelengths and captures image or live feed data by the image sensor, and where the control system is configured to monitor performance of the sectioning system as a function of the image or live feed data. In some embodiments, the present disclosure relates to a sectioning system, where at least one sensor is disposed on or in communication with the cutting assembly, and where the control system is configured to monitor the cutting assembly condition as a function of data from the at least one sensor. In some embodiments, the present disclosure relates to a sectioning system, where the control system is further configured to predict tissue section quality as a function of the monitored cutting assembly condition. In some embodiments, the present disclosure relates to a sectioning system, where the sectioning system further includes an imaging system including a lens and an imaging sensor configured to capture images, and a control system configured to analyze the images for blade artifacts and uniformity of tissue section thickness.In some embodiments, the present disclosure relates to a sectioning system, where the control system is configured to modify dynamic parameters and configuration of at least one of the chuck assembly or the cutting assembly without user intervention to compensate for deviating microtome conditions monitored from data from at least one sensor. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor includes a camera including a lens and a sensor configured to capture image or live feed data, and the control system is configured to predict tissue section quality as a function of the image or live feed data. In some embodiments, the present disclosure relates to a sectioning system, where the sectioning system further includes an illumination system configured to illuminate at least one of the chuck assembly or the cutting assembly at various wavelengths, and the controller is configured to monitor the cutting assembly condition without user intervention.

[0008] The present disclosure relates to a sectioning system including a tissue chuck configured to retain a tissue block therein, a blade configured to cut a tissue section from the tissue block, at least one sensor configured to sense dynamics of at least one of the tissue chuck or the blade, and a control system configured to receive sensed data from the at least one sensor, determine whether the sensed data exceeds predefined limits of baseline data, and output a signal if it is determined that the sensed data exceeds the predefined limits of the baseline data.

[0009] In some embodiments, the present disclosure relates to a sectioning system, where the signal includes at least one of an alert to a user, a control signal to suspend operation of the sectioning system, or a control signal to adjust an operating parameter of the sectioning system. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor includes a camera, where the camera includes a lens, and a sensor that captures images or live feed image data and monitors tissue section thickness in real time, and where the control system is configured to adjust the operating parameters of the sectioning system as a function of the images or live feed image data. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor includes a camera, where the camera includes a lens, a sensor, and a dedicated illumination system that provides illumination at various wavelengths and captures images or live feed data, and where the control system is configured to monitor the performance of the sectioning system as a function of the images or live feed data. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor includes a force sensor, the force sensor configured to collect vibration data from the sectioning system, and the control system configured to monitor performance of the sectioning system as a function of the vibration data. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor includes a laser Doppler vibrometer, the laser Doppler vibrometer configured to collect vibration data from the sectioning system, and the control system configured to monitor performance of the sectioning system as a function of the vibration data.

[0010] The present disclosure relates to a sectioning system including at least one sensor configured to sense data regarding the dynamics of one or more components of at least one of a chuck assembly or a cutting assembly, where the chuck assembly is configured to receive a tissue block and the cutting assembly is configured to remove a tissue section from the tissue block, and a controller in communication with the at least one sensor and configured to receive data from the at least one sensor, determine whether the data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly, and output a signal if it is determined that the data from the at least one sensor is not indicative of normal behavior of the one or more components.

[0011] In some embodiments, the present disclosure relates to a sectioning system, where the signal is a control signal to one or more components of at least one of a chuck assembly or a cutting assembly to adjust an operating parameter of the one or more components. In some embodiments, the present disclosure relates to a sectioning system, where the signal is an alert to a user. In some embodiments, the present disclosure relates to a sectioning system, where the signal is a control signal to suspend operation of the sectioning system. In some embodiments, the present disclosure relates to a sectioning system, where the controller is further configured to determine that the data does not indicate normal behavior of the one or more components when the data exceeds a predefined limit value of baseline data that indicates normal behavior of the one or more components. In some embodiments, the present disclosure relates to a sectioning system, where the controller is further configured to determine whether dynamics of the one or more components exceed a predetermined threshold within a selected frequency band and output a signal to correct a source of the dynamics that exceed the predetermined threshold. In some embodiments, the present disclosure relates to a sectioning system, wherein the at least one sensor is a camera including an image sensor configured to capture at least one of still images, video, or high speed images, and the data includes at least one of still images, video, or high speed images. In some embodiments, the present disclosure relates to a sectioning system, wherein the controller is further configured to actuate the motor, excite at least one of the chuck assembly or the cutting assembly with a predefined vibration signal, measure data with the at least one sensor, and obtain baseline data of at least one of the chuck assembly or the cutting assembly.In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is one or more of an image sensor, a video sensor, a high speed image sensor, a laser Doppler vibrometer, an acoustic sensor, or a force-based sensor. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is configured to capture images or live feed image data and monitor the performance of the sectioning system as a function of the images or live feed image data, and where the controller is configured to adjust operating parameters of at least one of a chuck assembly or a cutting assembly as a function of the images or live feed image data. In some embodiments, the present disclosure relates to a sectioning system, where the at least one sensor is an image sensor, and where the controller is further configured to control an illumination system to provide illumination at various wavelengths, capture images or live feed data by the image sensor, and monitor the performance of the sectioning system as a function of the images or live feed data.

[0012] The present disclosure relates to a method including receiving a tissue block in a chuck assembly; removing a tissue section from the tissue block with a cutting assembly; sensing with at least one sensor data related to dynamics of one or more components of at least one of the chuck assembly or the cutting assembly during removal of the tissue section from the tissue block; transmitting the sensed data by the at least one sensor to a controller; determining, by the controller, whether the sensed data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly; and outputting a signal if the controller determines that the data from the at least one sensor is not indicative of normal behavior of the one or more components.

[0013] In some embodiments, the present disclosure relates to a method further comprising: determining, by a controller, whether sensed data from the at least one sensor indicates a condition of one or more components of at least one of a chuck assembly or a cutting assembly that deviates from normal behavior; and outputting a signal if the controller determines that the data from the at least one sensor indicates a condition of one or more components of at least one of a chuck assembly or a cutting assembly that deviates from normal behavior. In some embodiments, the present disclosure relates to a method, where the determining step further comprises comparing, by the controller, the sensed data to baseline data, where the baseline data is indicative of normal behavior of the one or more components. In some embodiments, the present disclosure relates to a method, where the signal is a control signal to one or more components of at least one of a chuck assembly or a cutting assembly for adjusting an operating parameter of the one or more components. In some embodiments, the present disclosure relates to a method further including determining, by a controller, one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction, and outputting, by the controller, control signals to the one or more components that cause at least one of the chuck assembly or the cutting assembly to malfunction, adjusting operating parameters of the one or more components.In some embodiments, the present disclosure relates to a method further comprising: determining, by a controller, one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to not exhibit normal behavior; and outputting, by the controller, a control signal to another one or more components of at least one of the chuck assembly or the cutting assembly to adjust an operating parameter of the other one or more components. In some embodiments, the present disclosure relates to a method wherein the signal is an alert to a user. In some embodiments, the present disclosure relates to a method wherein the signal is a control signal to stop operation of a sectioning system comprising a chuck assembly and a cutting assembly. In some embodiments, the present disclosure relates to a method further comprising: determining, by a controller, baseline data indicative of normal behavior of the one or more components; wherein determining whether sensed data from at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly further comprises comparing, by the controller, the sensed data to the baseline data.

[0014] The present disclosure relates to a method including receiving, by a controller, sensed data using at least one sensor, the sensed data relating to dynamics of one or more components of at least one of a chuck assembly or a cutting assembly, the chuck assembly configured to receive a tissue block and the cutting assembly configured to remove a tissue section from the tissue block; determining, by the controller, whether the sensed data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly; and outputting a signal if the controller determines that the data from the at least one sensor is not indicative of normal behavior of the one or more components.

[0015] In some embodiments, the present disclosure relates to a method further comprising: determining, by a controller, whether sensed data from the at least one sensor indicates a condition of one or more components of at least one of a chuck assembly or a cutting assembly that deviates from normal behavior; and outputting a signal if the controller determines that the data from the at least one sensor indicates a condition of one or more components of at least one of a chuck assembly or a cutting assembly that deviates from normal behavior. In some embodiments, the present disclosure relates to a method, where the determining step further comprises comparing, by the controller, the sensed data to baseline data, where the baseline data is indicative of normal behavior of the one or more components. In some embodiments, the present disclosure relates to a method, where the signal is a control signal to one or more components of at least one of a chuck assembly or a cutting assembly for adjusting an operating parameter of the one or more components. In some embodiments, the present disclosure relates to a method further including determining, by a controller, one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction, and outputting, by the controller, control signals to the one or more components that cause at least one of the chuck assembly or the cutting assembly to malfunction, adjusting operating parameters of the one or more components.In some embodiments, the present disclosure relates to a method further comprising determining, by a controller, one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to not exhibit normal behavior, and outputting, by the controller, a control signal to another one or more components of at least one of the chuck assembly or the cutting assembly to adjust an operating parameter of the other one or more components. In some embodiments, the present disclosure relates to a method wherein the signal is an alert to a user. In some embodiments, the present disclosure relates to a method wherein the signal is a control signal to stop operation of a sectioning system including a chuck assembly and a cutting assembly. In some embodiments, the present disclosure relates to a method further comprising determining, by a controller, baseline data, the baseline data indicative of normal behavior of the one or more components, and determining whether sensed data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly further comprises comparing, by the controller, the sensed data to the baseline data.

[0016] These and other embodiments of the present disclosure are described in greater detail below. [Brief description of the drawings]

[0017] The presently disclosed embodiments will be further described with reference to the accompanying drawings, in which like structure is referred to by like numerals throughout the several views. The drawings shown are not necessarily to scale, with emphasis instead generally being placed upon illustrating the principles of the presently disclosed embodiments.

[0018] [Figure 1A]FIG. 1A is a top view of a sample system layout, according to some embodiments of the present disclosure.

[0019] [Figure 1B] 1B and 1C are isometric views of a sample system layout, according to some embodiments of the present disclosure. [Figure 1C] 1B and 1C are isometric views of a sample system layout, according to some embodiments of the present disclosure.

[0020] [Figure 2A] FIG. 2A is a side view of a sample system layout, according to some embodiments of the present disclosure.

[0021] [Figure 2B] FIG. 2B is a top view of a sample system layout, according to some embodiments of the present disclosure.

[0022] [Diagram 3] FIG. 3 is an exemplary high-level diagram of a feature tracking system according to some embodiments of the present disclosure.

[0023] [Figure 4] FIG. 4 is a graph illustrating tissue block displacement versus speed change at the interface between the tissue block and the microtome.

[0024] [Diagram 5] FIG. 5 is a block diagram illustrating a control feedback loop according to some embodiments of the present disclosure.

[0025] [Figure 6] FIG. 6 is a flow chart diagram of a sample method of operation according to some embodiments of the present disclosure.

[0026] [Figure 7]FIG. 7 is an exemplary high-level architecture for implementing a process according to the present disclosure.

[0027] [Figure 8A] 8A-8E are exemplary data of force measurements during slicing of a tissue block. [Figure 8B] 8A-8E are exemplary data of force measurements during slicing of a tissue block. [Figure 8C] 8A-8E are exemplary data of force measurements during slicing of a tissue block. [Figure 8D] 8A-8E are exemplary data of force measurements during slicing of a tissue block. [Figure 8E] 8A-8E are exemplary data of force measurements during slicing of a tissue block.

[0028] [Figure 9] FIG. 9 is a flowchart diagram of a sample method of operation according to some embodiments of the present disclosure.

[0029] Although the above-identified drawings set forth embodiments of the present disclosure, other embodiments are also contemplated as described in the discussion. The present disclosure presents illustrative embodiments by way of representation and not by way of limitation. Numerous other modifications and embodiments can be devised by those skilled in the art which fall within the scope and spirit of the principles of the presently disclosed embodiments. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0030] Detailed Description The present disclosure relates to a system and method for processing tissue blocks containing biological samples of tissue. Processing can include an automated system designed to section and cut tissue sections from tissue blocks using one or more microtomes. The cut tissue sections can be transferred to a transfer / transport medium such as tape and then transferred from the transfer medium to slides for pathology or histology examination. The disclosed method and system can be employed in conjunction with manual and automated microtomy methods and systems.

[0031] The present disclosure further provides methods and systems for improved prediction of defects in a microtome based on, for example, physical measurements. In some embodiments, the physical measurements can be determined from data from sensors located on the microtome or sensors monitoring the microtome itself. In some embodiments, the sensors may be on a chuck that holds the tissue block.

[0032] The present disclosure relates to systems and methods for identifying and / or predicting faults in a microtome or sectioning system. In some embodiments, one or more sensors collect data on one or more components of a microtome. The one or more components may be a chuck or other part of a chuck assembly of the microtome. The one or more components may be a blade, blade holder, or other part of a cutting assembly of the microtome. In some embodiments, one or more sensors collect data on a tissue block received in a tissue chuck. In some embodiments, one or more sensors can collect data on a static orientation of a tissue block, a part of a cutting assembly, or a part of a chuck assembly. In some embodiments, one or more sensors can collect data on dynamics of a tissue block, a part of a cutting assembly, or a part of a chuck assembly. As used herein, "dynamics" can refer to force, position, velocity, and / or acceleration at one or more time points, and / or changes in any of force, position, velocity, and / or acceleration over time, for example. In some embodiments, one or more sensors can collect data, such as thickness, regarding tissue sections cut by the microtome. The collected data can be compared to baseline data. The baseline data is generally data about the operation of the microtome in normal conditions. The microtome is in a normal state, for example, when all components are fastened together according to the design requirements of the microtome. That is, the baseline data relates to the expected orientation or dynamics of one or more components of the microtome or the tissue block when the microtome is operated in normal physical conditions. The baseline data can relate to tissue section quality (e.g., thickness) cut with a normal microtome (i.e., a microtome in a normal state or operating under normal conditions).In some embodiments, the sensor may collect data during standard operation of the microtome (i.e., when the microtome is being used to section a tissue block). In some embodiments, the microtome may be intentionally excited (e.g., vibrated or otherwise moved for purposes of collecting data), and the sensor may collect data during the excitation of the microtome.

[0033] The collected data can be analyzed and compared to baseline data. If the collected data meets or is within limits defined by the baseline data, the microtome can be determined to be in a normal condition. If the collected data deviates from the baseline data (e.g., exceeds limits defined by the baseline data), it can be determined that the microtome is not operating in a normal condition. The microtome may not be in a normal condition, for example, when one or more components of the chuck assembly and / or cutting assembly are loose or otherwise damaged. Tissue section quality can be degraded when the microtome is operating outside of normal behavior. If the microtome is determined to be not in a normal condition, the system can output a signal. In some embodiments, a specific cause of the microtome not being in a normal condition (e.g., a specific component that is loose) can be identified, and a signal can be to activate (e.g., tighten) one or more identified components to return the microtome to a normal operating condition. In some embodiments, a specific cause of the microtome not being in a normal state (e.g., a particular component that is loose) can be identified and a signal can be to activate one or more other components to account for the behavior of the identified faulty component (e.g., change the operation of the blade holder, account for faults in the blade), and return the microtome to a normal operating state. In some embodiments, the signal can be to suspend operation of the microtome. In some embodiments, the signal can be an alert to a user. The alert can inform the user that manual intervention is required to return the microtome to a normal operating state.

[0034] FIG. 1A is a top view of a sample system layout according to some embodiments of the present disclosure. FIG. 1B and FIG. 1C are isometric views of a sample system layout according to some embodiments of the present disclosure. FIG. 2A is a side view of a sample system layout according to some embodiments of the present disclosure. FIG. 2B is a top view of a sample system layout according to some embodiments of the present disclosure. FIG. 3 is an exemplary high-level diagram of a feature tracking system according to some embodiments of the present disclosure. FIG. 4 is a graph illustrating tissue block displacement vs. speed change at the interface between the tissue block and the microtome. FIG. 5 is a block diagram illustrating a control feedback loop. FIG. 6 is a flow chart diagram of a sample method of operation according to some embodiments of the present disclosure. FIG. 7 is an exemplary high-level architecture for implementing a process according to the present disclosure. FIGS. 8A-8E are exemplary data of force measurements while slicing a tissue block. FIG. 9 is a flow chart diagram of a sample method of operation according to some embodiments of the present disclosure.

[0035] In some embodiments, the present disclosure can be used in conjunction with tissue blocks containing biological samples such as tissue. The systems and methods of the present disclosure can be used to efficiently process and separate tissue blocks. Tissue samples are typically embedded in a preserving material such as paraffin wax or similar material. The embedding process can include any combination of processes for producing tissue blocks designed to be cut by the microtome 104. For example, the biological sample can be enclosed in a mold in addition to a liquid substance such as wax or epoxy that can harden to produce a block of the desired shape. Once the tissue blocks are generated, they can be inserted into the automated system 100 for cutting into tissue sections that can be placed on slides for viewing.

[0036] In particular, as discussed in more detail below, the automated system 100 is designed to receive one or more tissue blocks, each tissue block comprising a tissue sample embedded within an embedding or preservation material. The tissue blocks are delivered to one or more microtomes 104. The one or more tissue blocks are then "sectioned" using one or more microtomes 104 by removing a layer of preservation material in which the tissue sample is embedded, exposing a large cross-section of the tissue sample, e.g., the front surface of the tissue sample. Such exposed surface of the tissue sample of the tissue block is referred to as the block face. Once the tissue block is sectioned, the tissue block can be hydrated and cooled prior to sectioning the tissue block (cutting tissue sections that can be mounted on slides for viewing). One or more tissue sections, including a portion of the tissue sample, can then be sliced ​​from the sectioned tissue block using one or more microtomes 104. The tissue sections are transferred from one or more microtomes 104 to slides for further processing, for example, using an automated transfer medium.

[0037] 1A, 1B, and 1C, in some embodiments, an automated pathology system 100 is provided for preparing slides of tissue sections. Such a system can be configured for increased throughput during tissue sectioning. The system 100 can be designed to include a block handler 102, one or more microtomes 104, a transport medium 106 (e.g., tape), a hydration chamber 108, and a block tray 110. The block tray 110 can be a drawer-like device designed to hold multiple tissue blocks and can be placed in the system 100 for access by the block handler 102. The block tray 110 can have multiple rows, each designed to hold one or more tissue blocks, and can be sufficiently spaced so that the block handler 102 can deliver, grip, and remove one tissue block at a time. In some embodiments, the block tray 110 can be designed to securely hold the tissue blocks so that they do not shift or fall out of the block tray 110 during handling, for example, by using a spring-loaded mechanism. In some embodiments, the spring-loaded mechanism can further be designed to allow the block handler 102 to pull the tissue blocks without damaging or deforming them. For example, the pitch of the tissue blocks in the block tray 110 can allow the block handler gripper of the block handler 102 to access the paraffin blocks without interfering with adjacent blocks. The block handler 102 can include any combination of mechanisms capable of gripping and / or moving the tissue blocks in and out of the microtome 104, specifically into the chuck 250 (FIG. 2A) of the microtome 104. For example, the block handler 102 can include a gripper on a gantry, a push and pull actuator, or a selectively compliant assembly robotic arm (SCARA) robot.

[0038] 1A, 1B, and 1C, in some embodiments, system 100 can include a combination of mechanisms for transferring tissue sections cut from a tissue block onto a transport medium 106 to be transferred to slides for analysis. The combination of mechanisms can include a slide adhesive coater 112, a slide printer 114, a slide input rack 116, a slide singulator that picks slides from a stack of slides 118, and a slide output rack 120. This combination of mechanisms cooperate to prepare the tissue sections on the slides and to prepare the slides themselves.

[0039] In some embodiments, the one or more microtomes 104 can include any combination of microtome types known in the art, specifically for precisely sectioning tissue blocks. For example, the one or more microtomes 104 can be rotary, cryomicrotome, ultramicrotome, vibration, saw, laser, etc. based designs. In some embodiments, the one or more microtomes 104 can include a chuck assembly 251 and a cutting assembly 252, as shown in FIG. 2A. In some embodiments, the chuck assembly 251 and the cutting assembly 252 can move up and down along a vertical axis (i.e., in the Z direction shown in FIG. 2A), axially along a horizontal axis (e.g., in the direction of the thickness of the tissue block, i.e., in the X direction shown in FIG. 2A), laterally (i.e., in the Y direction shown in FIG. 2A), and / or rotationally relative to one another. In some embodiments, the chuck assembly 251 can move in three directions relative to the cutting assembly 252. The one or more microtomes 104 can include any combination of components for receiving and sectioning a tissue block. For example, the one or more microtomes 104 can include a knife block with a blade handler for holding an interchangeable knife blade and a sample holding unit with a chuck head and chuck adapter for holding a tissue block. The cutting assembly 252 can generally include a blade 270 (FIG. 2A) and a blade holder 260 (FIG. 2A). The chuck assembly 251 can generally include a chuck 250 (FIG. 2A).

[0040] In some embodiments, the one or more microtomes 104 are configured to cut tissue sections from a tissue sample that is encapsulated in a support block of a preserving material such as paraffin wax. The one or more microtomes 104 can hold a blade 270 (FIG. 2A) that is aligned to cut a tissue section from one face of the tissue block, i.e., the block cutting face or face. For example, a rotary microtome can linearly oscillate a chuck 250 that holds a tissue block with the block cutting face in the blade cutting plane, which, combined with incremental advancement of the block cutting face into the cutting plane, can cause the microtome 104 to continuously chip away thin tissue sections from the block cutting face. The blade 270 is specifically discussed in detail herein, but it should be understood that the same description can apply to any other cutting mechanism that may be included in a microtome.

[0041] In operation, the one or more microtomes 104 are used to section and / or slice a tissue block. When a tissue block is initially delivered to the one or more microtomes 104, the tissue block can be sectioned. Sectioning is the removal of a layer of preservation material from the tissue block to expose a large cross-section of the tissue sample to be embedded within the tissue block. That is, the preservation material in which the tissue sample is embedded can first be sectioned with relatively thick sections to remove a 0.1 mm to 1 mm layer of paraffin wax above the tissue sample. Once sufficient paraffin has been removed to expose the complete contours of the tissue sample, the block is "sectioned" and ready for access to processable tissue sections that can be placed on glass slides. The exposed surface is referred to as the block face or block cut surface. With respect to the sectioning process, the one or more microtomes 104 can chip away sections of the tissue block until an acceptable portion of the tissue sample within the tissue block is exposed. In some embodiments, the system can include one or more cameras to identify when an acceptable portion of the tissue sample in the tissue block is revealed. Regarding the cutting process, one or more microtomes 104 can shave off a section of the tissue sample of the tissue block with an acceptable thickness to be placed on a slide for analysis.

[0042] Once the tissue block has been sectioned, in some embodiments, the sectioned tissue block can be hydrated in a hydration fluid for a period of time (e.g., in the hydration chamber 108 or directly in the one or more microtomes 104). In addition to being hydrated, the tissue block can be cooled. The cooling system can be part of the hydration chamber 108 or a separate component from the hydration chamber 108. In some embodiments, the cooling system can provide cooling to all components in the sectioning chamber 150. The sectioning chamber 150 can provide insulation that encapsulates the one or more microtomes 104, the hydration chamber 108, the block tray 110, the blade holder and blade changer of the microtome 104, and the camera. In this way, there is a minimal number of openings in the insulation, which can improve efficiency and effectiveness in the sectioning chamber 150. Regardless of the location, the cooling system can have a mini-compressor, a heat exchanger, and an evaporator plate to generate a cold surface. Air in the sectioning chamber 150 can be drawn into and passed across the evaporator plate, for example, using a fan. Cooled air can be circulated within the sectioning chamber 150 and / or hydration chamber 108 to cool the paraffin tissue block. The mass of the equipment within the cooling chamber can provide thermal inertia as well. Once the chamber is cooled, its temperature can be more effectively maintained, for example, if an access door is opened by a user to remove the block tray 110. In some embodiments, the temperature of the tissue block is maintained between 4° C. and 20° C. Keeping the tissue block cool can benefit the sectioning and hydration processes.

[0043] Once the tissue block is sufficiently hydrated, in some embodiments, it is ready for sectioning. Essentially, one or more microtomes 104 cut thin sections of tissue samples from the tissue block. The tissue sections can then be picked up by a transport medium 106, such as tape, for subsequent transport for placement on a slide. In some embodiments, depending on the configuration of the microtomes 104 of the system 100, the system 100 can include a single or multiple transport medium 106 units. For example, in tandem operation, a transport medium 106 can be associated with the polishing and sectioning microtome 104, while in parallel operation, a separate transport medium 106 can be associated with each microtome 104 in the system 100. In some automated systems, each of these processes / steps of sectioning, hydration, sectioning, and transfer to slides are computer controlled rather than being performed in a manual workflow by a histotechnologist.

[0044] Still referring to Figures 1A, 1B, and 1C, in some embodiments, the transport medium 106 can be designed in a manner that tissue sections cut from tissue samples in tissue blocks can adhere to and then be transported by moving the transport medium 106. For example, the transport medium 106 can include any combination of materials designed to physically (e.g., electrostatically) and / or chemically adhere to tissue sample materials (e.g., tissue sections). The transport medium 106 can be designed to accommodate multiple tissue sections to be transferred to slides for evaluation. In some embodiments, the transport medium 106 can be replaced by a water channel for transporting the tissue. The system 100 can include any additional combination of features for use in automated microtome designs.

[0045] In some embodiments, the system 100 can follow a process for sectioning, hydrating, sectioning tissue sections, and transporting the cut tissue sections to slides in an efficient, automated manner.

[0046] In some embodiments, the system 100 can predict the cutting quality of a given microtome 104 based on one or more physical measurements using at least one sensor during operation of the microtome 104. Predicting the cutting quality of the microtome 104 can be advantageous to prevent any damage to the tissue section, as opposed to adjusting only the microtome 104, such as the blade 270 (FIG. 2A) and / or the chuck 250 (FIG. 2A) that holds the tissue block after damage to the tissue section is found. Furthermore, by preemptively preventing departures from a baseline physical state (i.e., the normal operating state of the microtome 104), the automated system 100 can predict variations in tissue quality before they occur. Such a system can prevent unnecessary waste of tissue and allow for more efficient use of biopsy samples.

[0047] In some embodiments, as shown in FIGS. 2A and 2B, a set of one or more sensors can provide information regarding the integrity of the microtome 104. In some embodiments, the set of one or more sensors can include an accelerometer 255. The accelerometer 255 can be referred to as a force-based sensor. For example, the accelerometer 255 can be disposed on the chuck 250 or other portion of the chuck assembly 251. The accelerometer 255 can be provided to measure the dynamics of the chuck 250 or other portion of the chuck assembly 251. The accelerometer can detect a breakaway or change in a motion characteristic of the chuck 250 or other portion of the chuck assembly 251. The motion characteristic can be, by way of example, a range of positions of the chuck 250 or other portion of the chuck assembly 251 during normal use. A departure in the motion characteristic (e.g., a deviation in the range of motion compared to the range of motion of the chuck 250 or other portion of the chuck assembly 251 under normal operating conditions) may indicate a loose part in the chuck 250 or any other fastener in the local system, such as the chuck assembly 251. A loose part in the chuck 250 or other fastener in the local system may generate unwanted relative motion between the chuck 250 and a tissue block received in the chuck 250, thereby degrading the cut quality of the microtome 104 when sectioning the tissue block. In some embodiments, the accelerometer 255 may additionally measure the static state or orientation of the microtome 104, e.g., to determine the relative orientation of the microtome 104 with respect to other structures in the system 100. In some embodiments, the accelerometer may measure the static state or orientation of the chuck 250 or other portion of the chuck assembly 251, e.g., to determine the relative orientation of the chuck 250 or other portion of the chuck assembly 251 with respect to other structures in the microtome 104. The accelerometer 255, in some embodiments, can measure low frequency vibrations, DC vibrations, or zero order changes. The accelerometer 255 can be used in combination with any of the other sensors discussed herein.For example, as discussed herein, in some embodiments, the set of one or more sensors can be one or more of an optical sensor, a video sensor, a high speed image sensor, a laser sensor, a load sensor, a strain gauge, and / or a microphone or acoustic sensor. Any one of these sensors can be configured, alone or in combination, to measure the static or dynamic condition of the microtome 104 or other structures in the system.

[0048] In some embodiments, the accelerometer 265 is present on the blade holder 260 or other portion of the cutting assembly 252 and can detect structural changes within the blade holder 260 or other portion of the cutting assembly 252. In some embodiments, the accelerometer 265 can detect changes in the motion characteristics of the blade holder 260 and / or other portion of the cutting assembly 252. The blade holder accelerometer 265 can be used in addition to the chuck accelerometer 255 or any other sensor discussed herein, or used alone. Depending on the location of the accelerometer 265, the stiffness of the crimp of the blade 270 can be detected as well. The accelerometer 265 can function similarly to the accelerometer 255 described above. For example, the accelerometer 265 can measure dynamics that may indicate loose parts within the blade holder 260 or other portion of the cutting assembly 252. In some embodiments, the accelerometer 265 can measure the static state or orientation of the blade holder 260 or other parts of the cutting assembly 252, for example, to determine the relative orientation of the blade holder 260 or other parts of the cutting assembly 252 with respect to other structures of the microtome 104 system.

[0049] In some embodiments, the microtome 104 system can be excited using motors at different frequencies to generate a frequency response function (FRF) and measure the dynamics of the microtome 104. In some embodiments, the motors can be stepper motors that make a buzzing noise. In some embodiments, a dedicated piezoelectric actuator can be installed on the microtome 104 system for more specific excitation. This excitation method can be used in other articles described below whenever excitation of the microtome 104 system is required. The motor 262 can be located in the microtome 104. Additionally or alternatively, there can be at least three motors for controlling the function of the microtome blade 270. At least three motors can be located in the cutting assembly 252. One of the three motors can be a microtome X motor 264 that can actuate the microtome blade 270 and determine the cut thickness. Another of the three motors can be a microtome Z motor 266 for actuating the microtome blade 270 for up and down cutting motions. The third actuator can be a blade clamp motor 268 on the blade holder 260. In an alternative to using the motor 262, the user can power these motors 264, 266, 268 so that they do not move about an axis, but buzz in place and generate vibrations in a known frequency range. This actuation can be the input vibration excitation to the microtome 104 system. These vibration waves travel through the microtome structure (e.g., the blade holder 260, the blade 270, or other parts of the cutting assembly 252) and can be picked up by a sensor, such as a microphone, accelerometer, or force meter, located on or near the microtome blade 270 or other parts of the cutting assembly 252. The vibration sensor can be used in combination with any of the other sensors discussed herein. The signal from the sensor is the output reading from the system. The output reading depends on the input excitation signal and the structural configuration of the microtome 104.For example, in the baseline case, when the microtome blade 270 is in normal operating condition and consistently cutting good quality tissue sections, the system can understand that all of the components are fastened together at the appropriate predefined torque. When the baseline configuration is excited (i.e., vibrated), the output readings can carry certain frequency components therein. Now, in a second configuration, the microtome 104 system can have loose parts or parts that have been modified differently due to general use or damage. The sub-optimal configuration can be excited such that the output readings will have a different set of frequencies contained therein compared to the output generated when exciting the baseline configuration. The signal processing step to detect these frequencies is called frequency analysis, and the signal processing step can generate a frequency response function (FRF), where the FRF is a power spectrum graph. The peaks that occur in the baseline FRF and the sub-optimal FRF may be at different frequencies, and by looking at the shifting peaks, it can be concluded that the microtome 104 performance is degraded. It is important to note that using FRFs is one exemplary method. In some embodiments, the system can employ AI to detect patterns, spot trends, and suggest solutions in time series or frequency domain data.

[0050] In particular, it should be understood that while exciting the cutting assembly 252 with one or more of the motors discussed in detail above, the same approach may be taken to excite the chuck assembly 251 and analyze the configuration or operating state of the chuck assembly. For example, a thickness axis motor may be attached to the chuck 250 or other portion of the chuck assembly 251 and, when buzzed, can generate an excitation vibration on the chuck 250 or other portion of the chuck assembly 251.

[0051] In some embodiments, a multi-axis force sensor 220 can be disposed on the microtome 104. The multi-axis force sensor 220 can be used to measure the dynamics of the microtome 104. In some embodiments, the multi-axis force sensor 220 can be disposed on the chuck 250 or other portion of the chuck assembly 251. The multi-axis force sensor 220, while detecting and measuring the magnitude and phase shift of the force acting on the chuck 250, can cut a reference material (not shown) and determine a baseline or expected set of data related to the normal operating condition of the chuck 250 or other portion of the chuck assembly 251 and compare against data collected during use of the microtome 104 to section a tissue block. The reference material can be a paraffin edge of a certain width of the block (before the tissue area is reached). Alternatively, the system can be excited by a buzzing motor or piezoelectric actuator to detect and measure a baseline of the expected force on the chuck 250 during use while in normal operating condition. As with independent excitation or excitation during use of the cutting assembly 252, as discussed above, an algorithm can compare deviations in peak frequency to a baseline and make decisions based on those deviations that depend on the specific microtome design characteristics and detection accuracy required for a given tissue sample. Although the chuck assembly 251 is specifically discussed above, it should be understood that the multi-axis force sensor 220 can be disposed on the blade holder 260 or other portion of the cutting assembly 252 and used in the same manner to measure forces acting on the blade holder 260 or other portion of the cutting assembly 252.

[0052] In some embodiments, in addition to or instead of the accelerometer 265, the system can use additional sensors to measure the dynamics of the microtome 104 (e.g., force, change in position, velocity, or acceleration). The additional sensors can measure the dynamics of one or more components of the chuck assembly 251 and / or the cutting assembly 252. The dynamics of the microtome blade 270 can be the way the blade 270 moves, including, for example, vibration level motion. The dynamics of the microtome blade 270 can include vibration characteristics such as the magnitude and frequency of acceleration. In some embodiments, these additional sensors can be used independently of the chuck accelerometer 255, accelerometer 265, and multi-axis force sensor 220. In some embodiments, there are methods to measure the dynamics of the microtome 104, such as the blade holder 260, without affecting the dynamics of the part being measured. For example, these sensors and methods may not change the stiffness or add mass to the system. Such sensors may use ultrasonic or laser measurements. For example, a laser sensor can be installed to measure vibrations of the blade 270 or blade holder 260. If the magnitude of these vibrations exceeds a certain threshold, or the FRF as described above deviates beyond a threshold, the system can determine that the cutting quality of the microtome 104 may be suspect. In some embodiments, the laser sensor can be a laser Doppler vibrometer.

[0053] In some embodiments, the system may include a linear encoder 210 for measuring motion information. The linear encoder 210 may be located within the chuck assembly 251. For example, a first portion of the linear encoder 210 may be coupled to a static base portion of the chuck assembly 251, and a second portion of the linear encoder 210 may be coupled to the moving, chuck 250. The resolution of the linear encoder 210 may be in the range of 50 nm to 100 nm, depending on the system. The linear encoder 210 may detect vibrations and precise axis positioning. A benefit of the linear encoder 210 is that there is little added mass to the system. The linear encoder 210 may be used in combination with any of the other sensors discussed herein. Although an implementation with the chuck 250 is specifically discussed above, it should be understood that the linear encoder 210 may be located within the cutting assembly 252 and sense the displacement or vibration of the blade holder 260, for example, or other portions of the cutting assembly 252.

[0054] In some embodiments, the system can include a non-contact reflective laser sensor 230 for measuring dynamic and / or static information. In some embodiments, the non-contact reflective laser sensor 230 can be positioned such that it is directed toward one or more components of the chuck assembly 251 and / or the cutting assembly 252. With respect to the cutting assembly 252, for example, the non-contact reflective laser sensor 230 can be positioned such that it is directed toward the microtome blade 270 and detects vibrations on the blade 270. It should be understood that the non-contact reflective laser sensor 230 can be used to detect vibrations of the chuck 250, for example. The system can generate an alert when the vibrations are outside of an acceptable range. The non-contact reflective laser sensor 230 can be used in combination with any other sensor discussed herein.

[0055] In some embodiments, the sectioning system can include a high-speed camera 215 for dynamic or static measurements. In some embodiments, the high-speed camera 215 can measure vibrations. For example, the high-speed digital camera 215 can be used to take multiple pictures per second and compare location information from the pictures to determine relative locations of the microtome 104 components and measure vibration offsets. In some embodiments, the high-speed camera 215 can be focused on one or more components of the chuck assembly 251 and / or the cutting assembly 252. For example, the high-speed camera 215 can be focused on the blade 270 and detect vibrations of the blade 270 during cutting. In some embodiments, vibrations in the blade 270 can be detected in a non-invasive manner, for example, by exciting the blade holder 260 in a controlled manner and using the high-speed camera 215. For example, the camera 215 can be angled relative to a point on the microtome 104, as generally shown in FIG. 1C. In some embodiments, the data derived from the high-speed camera 215 can be displacement data. In some embodiments, images from the high speed camera 215 can be used to determine acceleration data, which can be used in conjunction with the displacement data to predict the cutting quality of the microtome 104. For example, the system can define a normal motion profile (i.e., a baseline motion at which the component under test should operate during normal conditions), and if the measured displacement falls outside of the normal motion profile, the cutting quality of the microtome 104 can be assumed to be suboptimal. The high speed camera 215 can be used in combination with any other sensor discussed herein.

[0056] In some embodiments, one or more high speed cameras 215 can be used to trace marker pixels throughout the movement of the tissue block 500 during the sectioning process. Data collected by the high speed camera 215 can be used to determine, for example, the speed of the tissue block 500 along one or more axes. The axes of movement in the X and Z directions shown in FIG. 3 correspond to the coordinates shown in FIG. 2A. In the illustrated embodiment, the X movement can correspond to the axial movement of the chuck 250 and thus the tissue block 500. Additionally, the Z movement can correspond to, for example, the vertical movement of the microtome blade 270 during cutting. In operation, as shown in FIG. 3, sample pixels can be picked to trace the tissue block 500. Features tracked along sequential high speed camera (HSC) images allow detailed tracking of movement in both the vertical and axial directions. For example, a "high intensity" reflection 510 of a wax feature on the tissue block 500 can be 1-2 pixels in size. In use, the system may have pixel count variance, and pixel count variance in a given direction may be due to changes in speed, cut thickness, or depth within the tissue block 500. Pixel count variance is generally related to the number of pixels that the reflection moves through in the high speed camera image. For example, the camera 215 may remain stationary so that the pixels in the image move along with the tissue block 500, and the speed of pixel movement may be calculated based on the frame rate, magnification, and pixel position within the image data. Pixel count variance in the axial direction may be due to tissue block 500 variation in position along the axial direction (i.e., changes in cut depth on the wax / tissue of the tissue block 500). In some examples, the interaction of the blade 270 with the paraffin or tissue block 500 may result in an instantaneous change in speed, which may be recovered in the next cycle. One or more high speed cameras 215 may be used in combination with any other sensor described herein.

[0057] In FIG. 4, a graph of the speed of a selected pixel or point is shown. The cutting can be due to the movement of the microtome 104 in the Z-axis (i.e., the movement of one or both of the blade 270 or the chuck 250 along the Z-axis to generate a relative movement between the blade 270 and the chuck 250 in the Z-direction). In some embodiments, the camera 215 can be a high-speed camera that can determine the change in speed of one or more components of the microtome 104 and the change in displacement of the tissue block 500, for example, at the blade 270, during the cutting of the tissue block 500 at various speeds, such as, for example, 540-580 fps or 560 fps. The top plot of the graph in FIG. 4 shows the movement of the tissue block 500 in the X-direction, and the plot at the bottom of the graph shows the speed change in the Z-direction. In the illustrated example, the relative axes are marked in FIG. 3. 3 can show the deceleration or transition when tissue block 500 may impact blade 270 or when blade 270 transitions from paraffin to tissue embedded within paraffin. In this example, the transition is shown at frame steps 9 and 19, as seen in FIG.

[0058] This data can be useful to determine or predict if there is a problem with the system, such that poor cut quality can be expected. For example, if the tissue chuck 250 or other portion of the microtome 104 is loose, the change in translation and / or speed of the tissue block 500 can be outside of the expected range 402. The expected range 402 can be relative to the baseline data and can indicate the expected range of motion of the tissue block 500 during normal operation of the microtome 104. Looking at frame step 9, the pixel displacement can be outside of the expected range 402. In some embodiments, any pixel displacement outside of the expected range can be analyzed as an indication that the microtome 104 is not operating under normal conditions and the system can take action to correct the microtome 104. In some embodiments, the system may analyze the pixel displacement data for expected deviations 404 outside of the expected range 402. 4, at frame step 9 or 19, the pixel displacement may be inside the expected deviation 404, shown as a dashed line, in which case the algorithm may determine that the system is in an operational condition. For example, because the displacement did not exceed the expected deviation 404 while outside of the normal operating condition, the system may determine that the microtome 104 is still in an operational condition and continue operation until the displacement exceeds the expected deviation 404, at which point the system may take action to correct the microtome 104. For example, if the pixel displacement is outside the expected deviation 404 at frame step 9 or 19, the algorithm may determine that the system requires maintenance to prevent damage to the tissue block 500.

[0059] Consideration of any changes or repairs to the system while it is in operation will depend on the type of problem detected within the microtome 104. For example, if a loose blade clamp is detected, the blade clamp motor may be overdriven. In another embodiment, if a loose chuck 250 is detected, the speed of the cut may be changed to temporarily maintain cut quality before the problem can be mechanically corrected. This would allow the system to be operational until it can be corrected by on-site maintenance.

[0060] Using the algorithm or tool, the system can track the build quality of the microtome by at least one of: (1) measuring the speed variance of the microtome versus the microtome sensor data; (2) measuring the paraffin block placement variance versus the holder and spring performance; and (3) setting performance requirements to test and validate against. For example, using a high speed camera (HSC), such as camera 215, pixel data from the imaging system can track the build quality of the microtome by at least one of: (1) measuring the speed variance of the microtome versus the microtome sensor data; (2) measuring the paraffin block placement variance versus the holder and spring performance; and (3) setting performance requirements to test and validate against. Each microtome can be tested against individual predefined design performance requirements within which the microtome should operate when healthy.

[0061] In embodiments where the speed dispersion of the microtome is measured against the microtome sensor data, the system may employ optical measurements using one or both of the cameras 215, 115 to obtain optical test data to confirm and compare with the microtome sensor data (i.e., any of the sensor data described above or below from a sensor other than the camera 215, 115) for speed dispersion, for example, in the Z direction of FIG. 2A. In some embodiments, the optical measurement data coincides in time with the movement of the tissue chuck 250 towards the blade 270 in the X direction. If the amplitude of the relative motion determined from the microtome sensor data, including any of the sensor data described above or below, is outside of a defined boundary of magnitude, frequency, or other physically relevant analytical quantity, the system may notify the user that the microtome 104, e.g., the blade 270 or the chuck 250, is trending outside of a predefined or defined limit (i.e., trending outside of normal operating conditions). In some embodiments, the sensed motion characteristics may indicate the influence of the paraffin block and the microtome blade 270. In some embodiments, the camera 215, 115 can be one of a high-speed, still image, or video camera or similar imaging sensor.

[0062] In some embodiments where paraffin block placement variance is measured relative to tissue chuck 250 and associated spring performance, the optical test data can verify that the tissue block is secured in a known position within tissue chuck 250 and that the spring strength of tissue chuck 250 is behaving according to design requirements. For example, optical test data from high speed camera 215 can indicate movement variance outside of an acceptable range and therefore indicate that microtome 104 is not in normal operating condition and whether the spring is set too weakly, set incorrectly, or has failed.

[0063] In some embodiments, the system can set expected performance requirements against which it can be tested and validated. In some embodiments, a preliminary build of the system can be performed using a so-called "validated built microtome" of known quality (i.e., a normal microtome or a microtome under normal operating conditions) to perform initial testing (e.g., sectioning a reference material) to obtain baseline or initial test data. In some embodiments, baseline test data can be established by establishing tissue cutting quality by sectioning tissue and performing the expected functions of the microtome 104 each time. The baseline data can be a metric against which manufactured microtome builds can be tested, and tracking software can be used to automate the capture of data and perform a comparison of actual data to the baseline data.

[0064] In some embodiments, the system can function with a closed loop control and condition monitoring system, as shown in FIG. 5. Such a system can capture input data from various sensors discussed above or below and input them into a device control computer, for example, system 1300 as shown in FIG. 7. In some embodiments, control and decision algorithms or non-transitory computer readable media can run on system 1300 to fuse the sensor data and make decisions regarding the condition of microtome 104 (i.e., whether microtome 104 is functioning under normal conditions or not) and cut quality. In some embodiments, the control system controls one or more components (e.g., actuators) of microtome 104 to compensate for any sensed degradation of microtome 104 performance. In some embodiments, the control system controls one or more components (e.g., actuators) to compensate for portions of microtome 104 that cause microtome 104 to behave outside of normal conditions. In some embodiments, the system may additionally or alternatively generate an alert to warn the user if self-correction is not sufficient or if user intervention is otherwise required.

[0065] In some embodiments, the system can additionally or alternatively include post-sectioning quality detection. For example, as tissue sections are taken on tape, in a continuous manner, ripples and other periodic marks are searched for and analyzed on the images of the tissue sections. The presence of such marks on the tissue sample can indicate loose parts in the microtome 104 or deterioration of sectioning quality. In addition, the system can measure the thickness of the tissue sections on the tape, determine section-to-section variations, and relate these to the structural integrity of the microtome 104. For example, the camera 115 can point to the tissue sections on the tape or glass, as generally seen in FIG. 1B, and determine the source of tissue quality deviations. In addition, the camera 115 can include a dedicated illumination system that can provide illumination at various predetermined wavelengths on demand. In some examples, tissue quality deviations can be determined using quality control algorithms such as those disclosed in commonly owned U.S. Application No. 17 / 451,870, entitled "FACING AND QUALITY CONTROL IN MICROTOMY," which is incorporated herein by reference in its entirety. These quality control algorithms can compare the first imaging data, i.e., a baseline image, to second imaging data acquired after cutting, identify correspondences in the tissue sample in the first imaging data and the second imaging data based on one or more quality control parameters, and determine cut quality or deviations or quality control issues in the microtome 104. The camera 115 can be used in combination with any other sensors described herein.

[0066] In some embodiments, the system can include additional sensors 130a, 130b, generally shown in FIG. 2B, but without regard to their specific location. For example, the sensor 130a can be a force-based sensor, such as a load cell. The force sensor 130a can be in-line, meaning that the load cell is mounted behind the sample chuck 250 and can detect any force applied to the tissue block held within the chuck 250. As discussed above, the system can perform analysis and detection using tools for acceleration and vibration data analysis with data from the sensor 130a. The force sensor 130a can be used in combination with any other sensor discussed herein.

[0067] In some embodiments, the system may additionally or alternatively include a sensor, which may be a temperature sensor 130b. The temperature sensor 130b may be a thermocouple or an IR temperature measuring device that is directed toward the tissue block or another reference surface. In some embodiments, as an example, if the temperature sensor 130b determines that the tissue block is reaching a temperature that exceeds a predetermined maximum value, the system may determine that the tissue is at risk of thermal damage and may alert the operator or automatically adjust one or more parameters or operations to correct the temperature. The temperature sensor 130b may be used in combination with any other sensor discussed herein.

[0068] Generally, as shown in FIG. 6, the system can be employed in a first step 1000 to sense data from one or more of the sensors described above (e.g., sensors 130a, 130b, 255, 265, and cameras 215, 115, etc., described above). As discussed above, the sensed data can relate to the dynamics of one or more portions of the chuck assembly 251, the dynamics of the tissue block received within the chuck 250, the dynamics of one or more portions of the cutting assembly 252, and / or the properties of the tissue section on the transport medium or slide. As discussed above, the sensed data can relate to the static orientation of the tissue block, portions of the cutting assembly 252, and / or portions of the chuck assembly 252. The data from the one or more sensors can then be transmitted in a second step 1010 to a local, i.e., remote, computing device.

[0069] In a third step 1020, the computing device may process the data from the one or more sensors with a control algorithm. The control algorithm may compare the sensed data to baseline data, which may be any value or limit, such as a predefined maximum or minimum value, a predefined range, and / or the like. The baseline data may generally relate to normal or baseline microtome 104 performance. If the control algorithm determines that the sensed data exceeds any predefined value of the baseline data, including, for example, a maximum or minimum value or a boundary of a predefined range, the computing device may generate an output signal in steps 1030, 1032, and / or 1034. Sensed data that exceeds a predefined value of the baseline data, such as a boundary, maximum, or minimum value, which may collectively be referred to as a limit value of the baseline data, may indicate that the microtome is not operating under normal conditions. In some embodiments, the sensed data can be analyzed for trends and it can be determined that the sensed data indicates that the microtome 104 is operating under normal conditions, but that the operating conditions are deviating outside or toward the limits of normal operating conditions. In such embodiments, if the control algorithm determines that the sensed data is deviating outside of the normal baseline data, the computing device can generate an output signal at steps 1030, 1032, and / or 1034.

[0070] If the sensed data determines that the microtome 104 is outside and / or deviating from normal conditions, the output signal in step 1030 can be a control signal to an actuator in the system 100 (e.g., an actuator in the chuck assembly 251 and / or the cutting assembly 252) to correct the microtome 104 or modify parameters of the automated tissue sample sectioning to compensate for the sensor readings indicating operation outside or deviating from normal operating conditions. In some embodiments, the control algorithm can issue a signal for corrective action. In some embodiments, the corrective action can be automated by the system 100. For example, the control algorithm may sense dynamics of the microtome 104 outside of an acceptable range, indicating, for example, that a bracket holding the chuck 250 needs to be tightened, and the system may output a control signal to tighten the bracket. That is, the system can output a control signal to directly correct the cause of the microtome not operating under normal conditions. In some embodiments, the control algorithm can issue a signal for a compensatory action. In some embodiments, the compensatory action can be automated by the system 100. For example, the control algorithm may sense dynamics of the microtome 104 outside of an acceptable range, indicating, for example, that a bracket holding the chuck 250 needs to be tightened, and the system may output a control signal to adjust the operation of one or more drive motors of the chuck assembly 251 to compensate for the effects of the loose bracket and return the microtome 104 to normal operating conditions (e.g., the speed at which the chuck is driven may be adjusted to compensate for the adverse effects of the loose bracket). That is, the system can output a control signal to compensate for the reason why the microtome is not operating under normal conditions.In some embodiments, interventions can be automated, such as, for example, where the control system can adjust the speed of sectioning of the tissue sample and correct identified operational malfunctions. The control signals can be for adjusting the speed, movement, or any other operational parameters of one or more components of the microtome 104.

[0071] In step 1032, the system can output a signal as an alert to the user. In some embodiments, an alert can be generated even when automated control is taken by the system, as described above in step 1030. For example, an alert can be to inform the user that a corrective or compensatory action has been taken by the automated system. In some embodiments, as an example, if the system based on the high speed camera 215 output determines that the tissue block has exceeded an allowable displacement value when the microtome blade 270 is engaged with the block, the system 100 can output an alert to the user of the device and stop operation if the deviation is large enough. In some embodiments, the system can output an alert to the user for manual adjustment of one or more components of the system 100 and / or the microtome 104 based on any baseline data that has deviated or been exceeded.

[0072] In step 1034, the control system may automatically output a control signal to stop operation of the microtome 104. The signal can be generated when the sensed data indicates that the microtome is not in or deviating from normal conditions. In some embodiments, the signal can be generated when the sensed data exceeds a limit value of the baseline data by a certain amount. In some embodiments, the signal can be generated when the rate of deviation of the data exceeds a certain rate. In some embodiments, the system may stop operation in step 1034 and simultaneously output an alert to the user in step 1032 indicating to the user that operation has been stopped. The system may stop operation until a human user can correct the underlying issue.

[0073] Data and control signals associated with the method of FIG. 6 can be communicated between sensors, a computing device, and one or more components (e.g., actuators) of the system 100 and / or microtome 104 via wired or wireless connections.

[0074] In some embodiments, the system may include an algorithm that uses data from one or more of the sensor outputs to reach a conclusion about the microtome 104 condition and cut quality prediction. For example, if the images from the tissue quality control camera 115 show a serrated edge of the blade on the tissue sample or tissue block, the system may determine that the blade 270 should be changed. At the same time, the force sensor 130a may record a stronger force due to the same serration or dulling of the blade 270. In another example, if the screws holding the pieces of the microtome 104 are loosening, the accelerometers 255, 265 on the microtome 104 may begin to record high frequency vibrations that were not present in past records. The algorithm may use decision trees to reach a conclusion based on data from multiple sensors. For example, the algorithm may modify the dynamic parameters and configuration of the chuck 250 and one of the blade 270 or blade retainer 260 to correct or compensate for deviations in the monitored microtome 104 conditions (i.e., if the microtome conditions deviate from normal to outside of normal). The algorithm may accomplish these modifications without human intervention, but may alert the user after completion of a given cut.

[0075] In general, as shown in FIG. 9, the system can be employed to determine baseline data from one or more of the sensors described above (e.g., sensors 130a, 130b, 255, 265, and cameras 215, 115, etc., described above). For example, in a first step 1100, a controller of the system can receive data from one or more of the sensors described above, for example, when sectioning a tissue block. As discussed above, the received data can relate to the dynamics of one or more portions of the chuck assembly 251, the dynamics of a tissue block received within the chuck 250, the dynamics of one or more portions of the cutting assembly 252, and / or characteristics of a transport medium or tissue section on a slide. As discussed above, the received data can relate to the static orientation of a tissue block, a portion of the cutting assembly 252, and / or a portion of the chuck assembly 252.

[0076] In a second step 1110, the controller may determine baseline data for the chuck assembly 251 and / or the cutting assembly 252 based on the received data. As discussed in more detail below, with respect to FIGS. 8A-8E, the controller may determine that a certain subset of the received data is the baseline data. The baseline data may be determined from the received data associated with cutting a tissue section from the tissue block, where the tissue section includes a complete cross-section of the tissue sample embedded within the tissue block. In other words, the received data associated with sectioning the tissue block or removing a slice of the tissue block may not be incorporated into the determined baseline data until a complete cross-section of the embedded tissue sample is exposed.

[0077] In a third step 1120, the controller may compare the subsequent sectioning data to the baseline data. In some embodiments, the subsequent sectioning data may relate to a subsequent tissue section removed from the same tissue block from which the system determined the baseline data. In some embodiments, the subsequent sectioning data may relate to a subsequent tissue section from a second tissue block different from the tissue block from which the system determined the baseline data. The comparison may be similar to that discussed with respect to step 1020 of FIG. 6.

[0078] In a fourth step 1130, the controller of the system may determine whether the microtome 104 or one or more components of the chuck assembly 251 and / or cutting assembly 252 are behaving normally based on the comparison in step 1120. If the microtome 104 is determined to be not behaving normally, the controller may generate any of the outputs discussed with respect to steps 1030, 1032, and 1034 of FIG.

[0079] 8A-8E, exemplary force data from one or more sensors described above while a tissue block is sectioned and sliced ​​are depicted. The Y-axis in the depicted graphs is force in Newtons acting on, for example, the chuck 250 or other part of the microtome 104. The X-axis is time. Slices of the tissue block can be taken, for example, 20 μm thick and cut at a speed of 100 μm / sec. FIG. 8A depicts a fourth cut of the tissue block measured from an initial sectioning cut of the tissue block. The dynamic profile of the microtome 104 within the slicing window 802 (i.e., the period during which the blade is slicing through the tissue block) is defined by a maximum force of about 1 N because the blade 270 encounters only a very small portion of the embedded tissue sample (i.e., the blade 270 has not yet sliced ​​through the complete cross section of the tissue sample). FIG. 8B depicts a ninth cut of the tissue block measured from an initial sectioning cut of the tissue block. The dynamic profile of the microtome 104 within the slicing window 804 is defined by a maximum force of about 1.4 N because the blade 270 encounters a larger portion of the embedded tissue sample than in the fourth cut. The force profile or shape within the slicing window 804 differs from that within the slicing window 802. FIG. 8C depicts the 43rd cut of the tissue block, measured from the initial sectioning cut of the tissue block. The dynamic profile of the microtome 104 within the slicing window 806 is defined by a maximum force of about 2.6 N because the blade 270 encounters a complete cross section of the embedded tissue sample. The force profile or shape within the slicing window 806 differs from that within the slicing windows 802 and 804. FIG. 8D depicts the 44th cut of the tissue block, measured from the initial sectioning cut of the tissue block. The dynamic profile of the microtome 104 within the slicing window 808 is defined by a maximum force of approximately 2.6N as the blade 270 encounters a complete cross section of the embedded tissue sample.The force profile or shape within slicing window 808 is different from those within slicing windows 802 and 804. The force profile or shape within slicing window 808 is similar to that of the forces within slicing window 806.

[0080] Baseline data can be generated from slicing windows 806 and / or 808, which generally indicates that the force dynamic profile (i.e., magnitude and shape of the curve) within the slicing window should remain relatively constant as the blade 270 slices through a complete cross-section of the tissue sample of the tissue block. For example, if during any subsequent slicing through a complete cross-section of the tissue sample, the force dynamic profile within the slicing window of the subsequent slice differs from that of the baseline, it can be determined that the microtome 104 is not operating under normal conditions. For example, if during any subsequent slicing through a complete cross-section of the tissue sample, the force dynamic profile within the slicing window of the subsequent slice begins to differ from that of the baseline, it can be determined that the microtome 104 is straying away from normal operating conditions. For example, FIG. 8E depicts the 60th cut of a tissue block, measured from an initial sectioning cut of the tissue block. The dynamic profile of the microtome 104 within the slicing window 810 is defined by a maximum force of about 4.0 N as the blade 270 encounters the complete cross section of the embedded tissue sample. Thus, the dynamic profile of the microtome 104 when performing the 60th slice is outside of the baseline data, as determined from and depicted in Figures 8C and 8D, indicating, for example, that the microtome 104 is no longer behaving normally. The force dynamic profile in subsequent slices may differ from the baseline data in terms of the magnitude of the force, the shape of the force plot within the slicing window under examination, or the size of the slicing window (e.g., the length of time required to complete the cutting of the tissue block).

[0081] Any suitable computing device may be used to implement the computing devices and methods / functionality described herein, and may be transformed into a specific system for performing the operations and features described herein through modifications of hardware, software, and firmware in a manner that significantly exceeds the mere execution of software on a typical computing device, as would be understood by one of ordinary skill in the art. An illustrative example of such a computing device 1300 is depicted in FIG. 7. The computing device 1300 is merely an illustrative example of a suitable computing environment and does not limit the scope of the present disclosure in any way. A "computing device" as represented by FIG. 7 may include a "workstation," a "server," a "laptop," a "desktop," a "handheld device," a "mobile device," a "tablet computer," or other computing device, as would be understood by one of ordinary skill in the art. Given that the computing device 1300 is depicted for illustrative purposes, embodiments of the present disclosure may utilize any number of computing devices 1300 in any number of different ways to implement a single embodiment of the present disclosure. Thus, embodiments of the present disclosure are not limited to a single computing device 1300, nor are they limited to a single type of implementation or configuration of an exemplary computing device 1300, as would be understood by one of ordinary skill in the art.

[0082] The computing device 1300 may include a bus 1310 that may be coupled, directly or indirectly, to one or more of the following illustrative components: memory 1312, one or more processors 1314, one or more presentation components 1316, input / output ports 1318, input / output components 1320, and power supply 1324. Those skilled in the art will appreciate that the bus 1310 may include one or more buses, such as an address bus, a data bus, or any combination thereof. Those skilled in the art will additionally appreciate that, depending on the intended application and use of a particular embodiment, multiple ones of these components may be implemented by a single device. Similarly, in some cases, a single component may be implemented by multiple devices. Thus, FIG. 7 merely illustrates an example computing device that may be used to implement one or more embodiments of the present disclosure and does not limit the present disclosure in any way.

[0083] Computing device 1300 may include or interact with a variety of computer-readable media. For example, computer-readable media may include random access memory (RAM), read-only memory (ROM), electronically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical or holographic media, magnetic cassettes, magnetic tapes, magnetic disk storage devices, or other magnetic storage devices that may be used to encode information and that may be accessed by computing device 1300.

[0084] The memory 1312 may include computer storage media in the form of volatile and / or non-volatile memory. The memory 1312 may be removable, non-removable, or any combination thereof. Exemplary hardware devices are devices such as hard drives, solid state memory, optical disk drives, and the like. The computing device 1300 may include one or more processors that read data from components such as the memory 1312, various I / O components 1316, and the like. The presentation component 1316 presents data indications to a user or other devices. Exemplary presentation components include display devices, speakers, printing components, vibrating components, and the like. The computing device 1300 may include one or more processors 1314 configured to execute instructions encoded on at least one non-transitory computer-readable storage medium. Execution of the instructions encoded on at least one non-transitory computer-readable storage medium may cause the one or more processors 1314 to perform one or more of the methods described above.

[0085] The I / O ports 1318 may allow the computing device 1300 to be logically coupled to other devices, such as I / O components 1320, some of which may be built into the computing device 1300. Examples of such I / O components 1320 include microphones, joysticks, recording devices, game pads, satellite dishes, scanning devices, printers, wireless devices, networking devices, and the like.

[0086] In some embodiments, a microtome system is provided that includes a sectioning device that includes one or more components, the sectioning device configured to receive a sample and configured to cut a section from the sample. The microtome system additionally includes at least one sensor configured to sense data regarding the dynamics of the sectioning device and one or more components of the control system. The control system is configured to receive data from the at least one sensor, determine whether the data from the at least one sensor is indicative of nominal or non-nominal behavior of the one or more components, and correct the source of the non-nominal behavior using human or automated intervention. In some aspects, the techniques described herein relate to a microtome system for controlling tissue section quality, the system including a tissue chuck configured to retain a tissue block therein, a microtome configured to cut a tissue section from the tissue block, at least one sensor configured to sense dynamics of one of the tissue chuck and the microtome, and a control system configured to receive sensed data from the at least one sensor and output one of an alert to a user, suspend operation of the robotic microtome system, and adjust operating parameters of the microtome system when the sensed data exceeds a predefined maximum or minimum value. ... and at least one sensor configured to sense dynamics of one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to sense dynamics of the one of the tissue chuck and the microtome, and at least one sensor configured to senseIn some aspects, the techniques described herein relate to a microtomy system for controlling tissue section quality, where one of the sensors in the system is a camera, the camera including a lens, a sensor, and a dedicated lighting system that provides illumination at various wavelengths and captures images or live feed data, and where a control system is configured to monitor the performance of the system as a function of the captured images or live feed data. In some aspects, the techniques described herein relate to a sectioning system for monitoring the health of a microtome, where the system includes a chuck for holding a sample, a microtome for cutting a portion of the sample, at least one sensor disposed on or in communication with the microtome, and a controller configured to monitor the health of the microtome as a function of data from the at least one sensor. In some aspects, the techniques described herein relate to a robotic sectioning system for monitoring health, where the imaging system includes a lens, an imaging sensor configured to capture images, and a controller configured to analyze the captured images for blade artifacts and uniformity of tissue thickness. In some aspects, the techniques described herein relate to a sectioning system for monitoring tissue section quality, the system including a chuck for holding a sample of tissue, a microtome for cutting tissue sections from the sample, at least one sensor in communication with the microtome, and a controller configured to monitor the health of the microtome as a function of data from the at least one sensor and predict tissue section quality as a function of the monitored microtome health. In some aspects, the techniques described herein relate to a sectioning system, the robotic sectioning system configured to modify motion parameters and configurations of one of the chuck and the microtome without user intervention to compensate for the monitored microtome health deviating from the at least one sensor.In some aspects, the techniques described herein relate to a robotic sectioning system, where at least one of the sensors is a camera including a lens and a sensor configured to capture images or live feed data, and where the controller is configured to predict tissue section quality as a function of the captured images or live feed data. In some aspects, the techniques described herein relate to a robotic sectioning system further including a dual illumination configured to illuminate the tissue sample at different wavelengths, and where the controller is configured to monitor the health of the microtome without user intervention.

[0087] Numerous modifications and alternative embodiments of the present disclosure will be apparent to those skilled in the art in light of the foregoing description. This description is therefore to be construed as illustrative only and is for the purpose of teaching those skilled in the art the best mode for carrying out the present disclosure. Details of construction may vary substantially without departing from the spirit of the present disclosure, and the exclusive use of all modifications that fall within the scope of the appended claims is reserved. Although the embodiments are described herein in a manner that allows a clear and concise specification to be written, it is intended and should be understood that the embodiments can be variously combined or separated without departing from the scope of the present disclosure. It is intended that the present disclosure be limited only to the extent required by the appended claims and the applicable rules of law.

[0088] As used herein, the terms "comprises" and "comprising" are intended to be interpreted as inclusive rather than exclusive. As used herein, the terms "exemplary," "example," and "illustrative" are intended to mean "serving as an example, instance, or illustration," and should not be interpreted as indicating or not indicating a preferred or advantageous configuration over other configurations. As used herein, the terms "about," "generally," and "approximately" are intended to cover variations that may exist at the upper and lower limits of ranges of subjective or objective values, such as variations in properties, parameters, sizes, and dimensions. In one non-limiting example, the terms "about", "generally", and "approximately" mean 10 percent or +10 percent or less, or -10 percent or less. In one non-limiting example, the terms "about", "generally", and "approximately" mean close enough to be considered included by one of ordinary skill in the art. As used herein, the term "substantially" refers to a complete or nearly complete extension or extent of an action, characteristic, property, state, structure, item, or result as would be understood by one of ordinary skill in the art. For example, an object that is "substantially" circular would mean that the object is either perfectly circular to mathematically determinable limits, or approximately circular as would be recognized or understood by one of ordinary skill in the art. The exact degree of acceptable deviation from absolute perfection may depend on the specific context in some cases.Generally, however, near perfection will be such that it has the same overall result as if absolute and total perfection were achieved or obtained. The use of "substantially" is equally applicable when utilized in the negative sense to refer to a complete or nearly complete lack of an action, property, quality, state, structure, item, or result, as would be understood by one of ordinary skill in the art.

[0089] It is also to be understood that the following claims are intended to cover all general and specific features of the disclosure described herein, and all terms of the scope of the disclosure that may be said to fall therebetween, as a matter of language.

Claims

1. 1. A sectioning system comprising: a chuck assembly configured to receive a tissue block; a cutting assembly configured to remove a tissue section from the tissue block; at least one sensor configured to sense data regarding dynamics of one or more components of at least one of the chuck assembly or the cutting assembly; 1. A control system comprising: receiving data from the at least one sensor; determining whether the data from the at least one sensor indicates normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly; outputting a signal when it is determined that the data from the at least one sensor does not indicate normal behavior of the one or more components; a control system configured to: A sectioning system comprising:

2. 10. The sectioning system of claim 1, wherein the signal comprises a control signal to one or more components of at least one of the chuck assembly or the cutting assembly for adjusting an operating parameter of the one or more components.

3. The sectioning system of claim 1 , wherein the signal comprises an alert to a user.

4. The sectioning system of claim 1 , wherein the signal comprises a control signal for suspending operation of the sectioning system.

5. The control system includes: receiving the data from the at least one sensor; determining that the data is not indicative of normal behavior of the one or more components when the data exceeds a predefined limit value of baseline data indicative of normal behavior of the one or more components; The sectioning system of claim 1 configured to:

6. The control system includes: determining whether the dynamics of the one or more components exceed a predetermined threshold within a selected frequency band; outputting a signal to correct the source of the dynamics that exceed the predetermined threshold; and The sectioning system of claim 1 configured to:

7. 2. The sectioning system of claim 1, wherein the at least one sensor comprises a camera including an image sensor configured to capture at least one of still images, video, or high-speed images, and the data comprises at least one of still images, video, or high-speed images.

8. a motor configured to excite at least one of the chuck assembly or the cutting assembly with a predefined vibration signal; Furthermore, 10. The sectioning system of claim 1, wherein the control system is configured to measure data using the at least one sensor to obtain baseline data for at least one of the chuck assembly or the cutting assembly.

9. The sectioning system of claim 1 , wherein the at least one sensor comprises one or more of an image sensor, a video sensor, a high-speed image sensor, a laser Doppler vibrometer, an acoustic sensor, or a force-based sensor.

10. 2. The sectioning system of claim 1, wherein the at least one sensor is configured to capture images or live feed image data and monitor performance of the sectioning system as a function of the images or live feed image data, and the control system is configured to adjust operating parameters of at least one of the chuck assembly or the cutting assembly as a function of the images or the live feed image data.

11. 10. The sectioning system of claim 1, wherein the at least one sensor includes an image sensor, the sectioning system further comprises an illumination system that provides illumination at various wavelengths and captures image or live feed data by the image sensor, and the control system is configured to monitor performance of the sectioning system as a function of the image or live feed data.

12. the at least one sensor is disposed on or in communication with the cutting assembly; The sectioning system of claim 1 , wherein the control system is configured to monitor a cutting assembly condition as a function of data from the at least one sensor.

13. 13. The sectioning system of claim 12, wherein the control system is further configured to predict tissue section quality as a function of the monitored cutting assembly condition.

14. 10. The sectioning system of claim 1, further comprising an imaging system including a lens and an imaging sensor, the imaging sensor configured to capture images, and the control system configured to analyze the images for blade artifacts and uniformity of tissue section thickness.

15. 2. The sectioning system of claim 1, wherein the control system is configured to modify dynamic parameters and configurations of at least one of the chuck assembly or the cutting assembly without user intervention to compensate for deviating microtome conditions monitored from the data from the at least one sensor.

16. 10. The sectioning system of claim 1, wherein the at least one sensor comprises a camera including a lens and a sensor, the sensor configured to capture images or live feed data, and the control system configured to predict tissue section quality as a function of the images or the live feed data.

17. 10. The sectioning system of claim 1, further comprising an illumination system configured to illuminate at least one of the chuck assembly or the cutting assembly at various wavelengths, wherein the control system is configured to monitor cutting assembly conditions without user intervention.

18. The at least one sensor includes a force sensor; the force sensor is configured to collect vibration data from the sectioning system; The sectioning system of claim 1 , wherein the control system is configured to monitor performance of the sectioning system as a function of the vibration data.

19. 1. A sectioning system comprising: a tissue chuck configured to retain the tissue block therein; a blade configured to cut a tissue section from the tissue block; at least one sensor configured to sense dynamics of at least one of the tissue chuck or the blade; 1. A control system comprising: receiving sensed data from the at least one sensor; determining whether the sensed data exceeds a predefined limit value of baseline data; outputting a signal when it is determined that the sensed data exceeds a predefined limit of the baseline data; a control system configured to: A sectioning system comprising:

20. 20. The sectioning system of claim 19, wherein the signal comprises at least one of an alert to a user, a control signal to suspend operation of the sectioning system, or a control signal to adjust an operating parameter of the sectioning system.

21. the at least one sensor includes a camera; the camera includes a lens and a sensor for capturing images or live feed image data and monitoring tissue section thickness in real time; 20. The sectioning system of claim 19, wherein the control system is configured to adjust operating parameters of the sectioning system as a function of the image or the live-feed image data.

22. the at least one sensor includes a camera; the camera includes a lens, a sensor, and a dedicated lighting system that provides illumination at various wavelengths and captures images or live feed data; 20. The sectioning system of claim 19, wherein the control system is configured to monitor performance of the sectioning system as a function of the image or live feed data.

23. the at least one sensor includes a force sensor; the force sensor is configured to collect vibration data from the sectioning system; 20. The sectioning system of claim 19, wherein the control system is configured to monitor performance of the sectioning system as a function of the vibration data.

24. the at least one sensor includes a laser Doppler vibrometer; the laser Doppler vibrometer is configured to collect vibration data from the sectioning system; 20. The sectioning system of claim 19, wherein the control system is configured to monitor performance of the sectioning system as a function of the vibration data.

25. 1. A sectioning system comprising: at least one sensor configured to sense data regarding the dynamics of one or more components of at least one of a chuck assembly or a cutting assembly, wherein the chuck assembly is configured to receive a tissue block and the cutting assembly is configured to remove a tissue section from the tissue block; and a controller in communication with the at least one sensor, receiving data from the at least one sensor; determining whether the data from the at least one sensor indicates normal behavior of one or more components of at least one of the chuck assembly or the cutting assembly; outputting a signal when it is determined that the data from the at least one sensor does not indicate normal behavior of the one or more components; a controller configured to: A sectioning system comprising:

26. 26. The sectioning system of claim 25, wherein the signal is a control signal to one or more components of at least one of the chuck assembly or the cutting assembly for adjusting an operating parameter of the one or more components.

27. 26. The sectioning system of claim 25, wherein the signal is an alert to a user.

28. 26. The sectioning system of claim 25, wherein the signal is a control signal to suspend operation of the sectioning system.

29. 26. The sectioning system of claim 25, wherein the controller is further configured to determine that the data does not indicate normal behavior of the one or more components when the data exceeds a predefined limit value of baseline data indicating normal behavior of the one or more components.

30. The controller further comprises: determining whether the dynamics of the one or more components exceed a predetermined threshold within a selected frequency band; outputting a signal to correct the source of the dynamics that exceed the predetermined threshold; and 26. The sectioning system of claim 25 configured to:

31. 26. The sectioning system of claim 25, wherein the at least one sensor is a camera including an image sensor configured to capture at least one of still images, video, or high-speed images, and the data includes at least one of still images, video, or high-speed images.

32. The controller further comprises: activating a motor to excite at least one of the chuck assembly or the cutting assembly with a predefined vibration signal; measuring data using the at least one sensor to obtain baseline data for at least one of the chuck assembly or the cutting assembly; 26. The sectioning system of claim 25 configured to:

33. 26. The sectioning system of claim 25, wherein the at least one sensor is one or more of an image sensor, a video sensor, a high-speed image sensor, a laser Doppler vibrometer, an acoustic sensor, or a force-based sensor.

34. the at least one sensor is configured to capture images or live-feed image data and monitor performance of the sectioning system as a function of the images or live-feed image data; 26. The sectioning system of claim 25, wherein the controller is configured to adjust operating parameters of at least one of the chuck assembly or the cutting assembly as a function of the image or the live feed image data.

35. the at least one sensor is an image sensor; The controller further comprises: controlling a lighting system to provide illumination at various wavelengths and capturing images or live feed data with said image sensor; monitoring the performance of the sectioning system as a function of the image or live feed data; 26. The sectioning system of claim 25 configured to:

36. 1. A method comprising: Receiving a tissue block within a chuck assembly; removing a tissue section from the tissue block using a cutting assembly; using at least one sensor to sense data regarding the dynamics of one or more components of at least one of the chuck assembly or the cutting assembly during removal of the tissue section from the tissue block; the at least one sensor transmitting the sensed data to a controller; the controller determining whether the sensed data from the at least one sensor indicates normal behavior of one or more components of at least one of the chuck assembly or the cutting assembly; the controller outputs a signal when it is determined that the data from the at least one sensor does not indicate normal behavior of the one or more components. A method comprising:

37. The at least one sensor includes a force sensor; 37. The method of claim 36, wherein the data sensed by the force sensor comprises vibration data from the chuck assembly or the cutting assembly.

38. determining whether the sensed data from the at least one sensor indicates a condition of the one or more components of at least one of the chuck assembly or the cutting assembly that deviates from normal behavior; outputting a signal when the controller determines that the data from the at least one sensor indicates a condition of the one or more components of at least one of the chuck assembly or the cutting assembly that deviates from normal behavior; 37. The method of claim 36, further comprising:

39. 37. The method of claim 36, wherein the determining further comprises the controller comparing the sensed data to baseline data, the baseline data indicative of normal behavior of the one or more components.

40. 37. The method of claim 36, wherein the signal is a control signal to one or more components of at least one of the chuck assembly or the cutting assembly for adjusting an operating parameter of the one or more components.

41. the controller determining one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction; the controller outputs control signals to the one or more components that cause at least one of the chuck assembly or the cutting assembly to exhibit abnormal behavior, adjusting operating parameters of the one or more components; 37. The method of claim 36, further comprising:

42. the controller determining one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction; the controller outputs control signals to one or more other components of at least one of the chuck assembly or the cutting assembly to adjust operating parameters of the one or more other components; 37. The method of claim 36, further comprising:

43. 37. The method of claim 36, wherein the signal is an alert to a user.

44. 37. The method of claim 36, wherein the signal is a control signal to stop operation of a sectioning system comprising the chuck assembly and the cutting assembly.

45. the controller determining baseline data indicative of normal behavior of the one or more components, wherein determining whether the sensed data from the at least one sensor is indicative of normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly further includes the controller comparing the sensed data to the baseline data.

37. The method of claim 36, further comprising:

46. 1. A method comprising: a controller receiving data sensed using at least one sensor; the sensed data relates to dynamics of one or more components of at least one of a chuck assembly or a cutting assembly; the chuck assembly is configured to receive a tissue block; the cutting assembly is configured to remove a tissue section from the tissue block; and the controller determining whether the sensed data from the at least one sensor indicates normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly; the controller outputs a signal when it is determined that the data from the at least one sensor does not indicate normal behavior of the one or more components. A method comprising:

47. determining whether the sensed data from the at least one sensor indicates a condition of the one or more components of at least one of the chuck assembly or the cutting assembly that deviates from normal behavior; outputting a signal when the controller determines that the data from the at least one sensor indicates a condition of the one or more components of at least one of the chuck assembly or the cutting assembly that deviates from normal behavior; 47. The method of claim 46, further comprising:

48. 47. The method of claim 46, wherein the determining further comprises the controller comparing the sensed data to baseline data, the baseline data indicative of normal behavior of the one or more components.

49. 47. The method of claim 46, wherein the signal is a control signal to one or more components of at least one of the chuck assembly or the cutting assembly for adjusting an operating parameter of the one or more components.

50. the controller determining one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction; the controller outputs control signals to the one or more components that cause at least one of the chuck assembly or the cutting assembly to exhibit abnormal behavior, adjusting operating parameters of the one or more components; 47. The method of claim 46, further comprising:

51. the controller determining one or more components of at least one of the chuck assembly or the cutting assembly that cause at least one of the chuck assembly or the cutting assembly to malfunction; the controller outputs control signals to one or more other components of at least one of the chuck assembly or the cutting assembly to adjust operating parameters of the one or more other components; 47. The method of claim 46, further comprising:

52. 47. The method of claim 46, wherein the signal is an alert to a user.

53. 47. The method of claim 46, wherein the signal is a control signal to stop operation of a sectioning system comprising the chuck assembly and the cutting assembly.

54. the controller further comprising determining baseline data; the baseline data is indicative of normal behavior of the one or more components; 47. The method of claim 46, wherein determining whether the sensed data from the at least one sensor indicates normal behavior of the one or more components of at least one of the chuck assembly or the cutting assembly further comprises the controller comparing the sensed data to baseline data.

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